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A Computational Approach to Uncovering Economic Growth Factors

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  • Mohsen Ahmadi

    (Urmia University of Technology)

Abstract

The knowledge-based economy is the basis of economics in which all businesses and industries benefit from the distribution and application of knowledge in pursuit of their goals to meet their needs. But the prosperity and growth of a knowledge-based economy can only be achieved if the economic, socio-political and legal frameworks of a country have the necessary background to realize the required indicators of a knowledge-based economy. In this paper, the economy growth-effected knowledge-based indicators are classified and prioritized using logarithmic fuzzy preference programming. Based on the results, the institutional and economic regime has the priority in comparison with other measures in economic growth. The results of prioritizing alternative criteria show that the technology foundation, structure of trained manpower, trade and capital, employment and economical trademark, respectively affect economic growth. Furthermore, the trade-related indicators are a low effect on economic growth, however, the technology-related indicators are most effective on it. Therefore, today’s oil and export economies are less prioritized than the application of knowledge, and in today’s world, the industrial economy cannot be advanced and must move towards a knowledge-based economy.

Suggested Citation

  • Mohsen Ahmadi, 2021. "A Computational Approach to Uncovering Economic Growth Factors," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1051-1076, December.
    • Handle: RePEc:kap:compec:v:58:y:2021:i:4:d:10.1007_s10614-020-09985-1
    DOI: 10.1007/s10614-020-09985-1
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    References listed on IDEAS

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    1. Stephen Oluwatobi & Isaiah Olurinola & Philip Alege & Adeyemi Ogundipe, 2020. "Knowledge-driven economic growth: the case of Sub-Saharan Africa," Contemporary Social Science, Taylor & Francis Journals, vol. 15(1), pages 62-81, January.
    2. Zeshui Xu & Hui Hu, 2010. "Projection Models For Intuitionistic Fuzzy Multiple Attribute Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 267-280.
    3. Adam P. Balcerzak & Michal Bernard Pietrzak, 2017. "Human Development and Quality of Institutions in Highly Developed Countries," Chapters, in: Mehmet Huseyin Bilgin & Hakan Danis, & Ender Demir & Ugur Can (ed.),Financial Environment and Business Development. Proceedings of the 16th Eurasia Business and Economics Society, edition 1, volume 1, chapter 18, pages 231-241, Institute of Economic Research.
    4. Sajjad Barkhordari & Maryam Fattahi & Naser Ali Azimi, 2019. "The Impact of Knowledge-Based Economy on Growth Performance: Evidence from MENA Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(3), pages 1168-1182, September.
    5. Mehmet Huseyin Bilgin & Hakan Danis & Ender Demir & Ugur Can (ed.), 2017. "Financial Environment and Business Development," Eurasian Studies in Business and Economics, Springer, number 978-3-319-39919-5, December.
    6. L Mikhailov, 2000. "A fuzzy programming method for deriving priorities in the analytic hierarchy process," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(3), pages 341-349, March.
    7. Islam, R. & Biswal, M. P. & Alam, S. S., 1997. "Preference programming and inconsistent interval judgments," European Journal of Operational Research, Elsevier, vol. 97(1), pages 53-62, February.
    8. Adel Ben Khalifa, 2019. "Direct and Complementary Effects of Investment in Knowledge-Based Economy on Innovation Performance in Tunisian Firms," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(2), pages 561-589, June.
    9. Chang, Da-Yong, 1996. "Applications of the extent analysis method on fuzzy AHP," European Journal of Operational Research, Elsevier, vol. 95(3), pages 649-655, December.
    10. Barker, Theresa J. & Zabinsky, Zelda B., 2011. "A multicriteria decision making model for reverse logistics using analytical hierarchy process," Omega, Elsevier, vol. 39(5), pages 558-573, October.
    11. Shouzhen Zeng & Jianping Chen & Xingsen Li, 2016. "A Hybrid Method for Pythagorean Fuzzy Multiple-Criteria Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 403-422, March.
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    Cited by:

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